In this paper, a new algorithm HCOUNT ＋ is proposed to find frequent items over data stream based on the HCOUNT algorithm. The new algorithm adopts aided measures to improve the precision of HCOUNT greatly. In additi...In this paper, a new algorithm HCOUNT ＋ is proposed to find frequent items over data stream based on the HCOUNT algorithm. The new algorithm adopts aided measures to improve the precision of HCOUNT greatly. In addition,HCOUNT ＋ is introduced to time critical applications and a novel sliding windows-based algorithm SL-HCOUNT ＋ is proposed to mine the most frequent items occurring recently.This algorithm uses limited memory （nB · （1 ＋α） · e/ε·In（-M/lnρ）（α〈1） counters）, requires constant processing time per packet （only （1＋α） · ln（-M/lnρ（α〈1）） counters are updated）, makes only one pass over the streaming data,and is shown to work well in the experimental results.展开更多
文摘In this paper, a new algorithm HCOUNT ＋ is proposed to find frequent items over data stream based on the HCOUNT algorithm. The new algorithm adopts aided measures to improve the precision of HCOUNT greatly. In addition,HCOUNT ＋ is introduced to time critical applications and a novel sliding windows-based algorithm SL-HCOUNT ＋ is proposed to mine the most frequent items occurring recently.This algorithm uses limited memory （nB · （1 ＋α） · e/ε·In（-M/lnρ）（α〈1） counters）, requires constant processing time per packet （only （1＋α） · ln（-M/lnρ（α〈1）） counters are updated）, makes only one pass over the streaming data,and is shown to work well in the experimental results.
